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Your Shopping Cart just got a whole lot Smarter, this festive season

Nivin Simon
7 minutes, 7 seconds read

The shopping season has officially returned to the Indian subcontinent. While the first phase of festivities (typically) kicks off with the onset of Navratri (sep 29) till Dussehra (oct 8), Indian retailers will have clocked above 40% of their annual sales within this ten day window alone. For consumers, ‘better deals’ take precedence over attributes like faster shipping during this season. In fact, retailers will have adjusted their pricing to strongly reflect these consumer preferences — a pair of women’s running shoes, for instance, will have a discounted price of 19% pre-diwali and upto a flat 50% discounted price on the day of. 

In a country with over 400M active online users, customer fealty during this season is even more fickle than usual. The growing number of online consumers are heralding new buying behaviors especially from tier 2 and 3 cities. According to Google Insights, 70% of Indian netizens go online during the festive season to browse products, compare prices, read reviews and look for deals. For brands & retailers, getting in front of these potential customers and clamoring for their attention is the pivotal moment of truth. 

Amazon and Walmart-owned Flipkart, India’s top two e-tailers, are using intelligent technologies to stave off each other’s aggressive discounting strategies. The two e-commerce giants have cumulatively created over 140,000 temporary jobs across supply chain, last-mile connectivity and customer support to handle the extra influx of trade. Daily shipments in India is expected to touch 4 million units during the ongoing festive season.

AI in e-commerce:India's e-retail market share of gross merchandise value.

Which begs the question: How are they doing this? How are they using technology to stay-on-top?

It’s no secret, the retail spend on AI is forecast to grow from $2 billion in 2018 to $7.3 billion by 2022, according to Juniper Research.
In reality, they rely on Artificial Intelligence — it is where these companies have primarily invested a huge chunk of change to enhance their business. By leveraging the right set of AI-assisted tools in their operations, they are able to retain and convert more customers. 

Artificial Intelligence and related technologies like machine learning and natural language processing has intensified over the digital buying landscape. This has forced brick & mortar stores including physical outlets with omni channel reach to a receding corner of the industry.

There’s more to the digital landscape than meets the eye. It is a space plagued with security concerns. E-commerce companies are using AI to detect and eliminate potential frauds on their platform. They’ve deployed AI models that constantly vets fraudulent accounts that have only signed up to make the most of promo codes, or bring cash out of stolen credit cards. 

Yes, aggressive pricing does work as reflected by the higher EMI adoption this year. However, cash burn through discounts is not the overhaul the industry can sustain itself on. Big Data Analytics can prescribe a more proactive approach for suggestions based on statistical association evaluation, time spent on site, cookies behavior and method of accessing site which can tell a brand the how, what and when of the customer buying cycle — in turn, increasing sales.

AI has even infiltrated physical retail, and is now helping stores maximise marketing efforts, personalise the customer experience and optimise their store inventory.

AI in retail market

Warehouses and stores, in India, are also making use of ‘Cobots (collaborative robots) to assist humans in performing tedious and repetitive shop-floor tasks. The cobots run on machine learning algorithms that have defined its capacity to perform specific tasks while also learning to get better with new data.

Ahead of this year’s festive sale, Flipkart has added 340 cobots or automated guided vehicles (AGVs) to its current fleet of 110. These bots can carry anything with them, from appliances to mobile phones. 

After the first phase of the festive shopping marathon, Amazon and Flipkart have both made significant wins over the period. They will look to extend their market capture as we move into the second phase of the season (Diwali).

Interestingly, for Amazon, almost half the product sales came from lower-tier urban areas. Amazon India-owned Echo products even saw a record 70 fold increase in sales.

Flipkart receives over 90% of traffic from its android app, and has designed its app home screen personalized to each of its 120 million+ customers. They have deployed machine learning models and algorithms on various customer data points like customer location, language, gender, price, affinity to a store or brand, purchasing frequency, purchase volume, price group, etc. among others.

These data points help Flipkart make predictions even without the customer being on their platform. Using these machine learning models they are also able to predict if a customer is going to return a particular product.

This season, customers can continue to expect strides in personalization and tailored experiences. E-tailers can expect to see improvements to their order handling, and personalization efforts. Overtime, these improvements will pay dividends in the form of revenue enhancement, increased margins, and higher sales.

How can AI upscale e-commerce

AI has made smooth inroads into digital shopping aisles — with several intelligent use cases such as stock assortment, fraud reduction and self-checkout. Here is a brief compilation of adopted strategies used in retail with the potential to disrupt the future of online shopping.

Product Recommendations

Recommendation engines have become a staple of commercial AI usage. By looking at customers’ purchase histories, current activity (cart contents and page views), and other linked third-party data, e-tailers can make highly tailored suggestions. Amazon, for example, makes more than 40% of its sales via their recommendation engine which also suggests items based on what your friends have purchased recently.Demand Forecasting
E-tailers expect to know in advance how much of each product is projected to especially during peak season. AI can enhance demand predictions by minimizing overstock and out-of-stock situations. ML Algorithms can optimise what products should be made available in a particular geography. For example, Levi’s is using AI to improve size availability, and Nike is using geographical and behavioural data from its app to inform store offerings.

Personalization

AI systems can capture deep customer insights about their buying preferences and behavior using their social data, purchase history, and browsing habits. AI can fill in the gaps by looking at a user’s spending patterns and other data sources to come up with a very detailed view of the customer. This has proven to enhance the customer’s digital shopping experience with a more satisfying view of highly relevant and hyper-personalized offerings.

Shopping Assistant

An AI-powered shopping assistant is a natural extension of the chatbot, with layers of visual processing added in. For example, if a customer wants to choose an outfit for a special occasion. The AI shopping assistant could learn their tastes and help them select some garments. It could then walk them through the process of virtually trying on an outfit (virtual trial rooms). It could offer suggestions for complementary items or encourage them to buy the product, as a friend might. The shopping assistant can also suggest the complementary outfits, footwear and accessories just like a real fashion assistant/advisor would.

Swift Customer Service

Primarily dominated by chatbots over the last several years, bots can learn from the interactions between customers and human reps. Chatbots are trained using natural language processing techniques to understand jargon and ‘speech’ specific to retail. They can then use the data it harvests to create a more personable interaction. It can also quickly reduce the number of touchpoints for the customer and help address immediate queries related to pricing, product availability, returns and recommendations without the need for human intervention.

Also read – How Chatbots are changing the digital Indian?

Smarter Voice Searches

Voice-powered searches can act on a ton of customer insights and information fed into the recommendation engine from the customer’s profile. Voice-activated shopping, is a natural extension of human behavior — allowing consumers to take control of the omnichannel experience to learn more about the product, gather quick product information, compare prices etc. Orders placed via Alexa have increased three times more than the year-ago festive shopping season.

Product identification & visual search

esearch has shown customers who gravitate towards voice-powered searches, equally embrace visual searches. For example, an AI-powered matching algorithm could look at the images of a customer’s favorite products (shirts, sneakers etc.) and suggest similar ones based on attributes like pattern, fit, color, style etc. The AI program can also identify products kept in cart and website pages from browsing based on the customers’ past shopping data and other data from various sources, making the suggestions more accurate with time.

To know more about how Artificial Intelligence can help increase your persona capture and retention, reach out to us on hello@mantralabsglobal.com.

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Chatbots are the assistants of the future and they are taking the Internet by storm. Ever since their first appearance in 1994, the goal was to create an AI that could conduct a real dialogue with their interlocutors. The purpose is to free up customer service agents’ time so they could focus on more delicate tasks- which require a more human approach.

If you are thinking about including a chatbot on your website, here are the things you need to keep in mind to boost customer engagement and deliver high-quality services.

Define your audience

First things first- think about who will be interacting with the chatbot? Who are your customers? How do they talk? How can you address them in a way they’ll enjoy? How can you help them?

For instance, if your company sells clothes that are mostly designed for young adults, using a less formal tone will be much more appealing to them.

Lisa Wright, a customer service specialist at Trust My Paper advice: “Customer service calls are usually recorded, so listening to a few of them can be a good place to start designing your chatbot’s lines of dialogue.”

Give your bot some character

People don’t like to talk to plain, simple robots. Therefore, giving your chatbot some personality is a must. Some brands prefer naming their chatbots and even design an animated character for them. This makes the interaction more real.

For example, The SmarterChild chatbot- designed back in 2000, was able to speak to around 2,50,000 humans every day with funny, sad, and sarcastic emotions.

However, the chatbot’s character needs to match your brand identity and at the same time- appeal to customers. Think about – how would the bot speak, if they were real? Are there some phrases or words they would never use? Do they tell jokes? All these need to be well-thought through, before going into the chatbot writing and design phase.

According to a report published by Ubisend in 2017, 69% of customers use the chatbot to get an instant answer. Only 15% of them would interact for fun. Thus, don’t sacrifice the performance for personality. 

Also read – 5 Key Success Metrics for Chatbots

Revise your goals before chatbot writing

Alexa- Amazon bot has 30+ skills which include scheduling an appointment, booking a cab, reading news, playing music, controlling a smartphone, and more. However, every business bot doesn’t need to be a pro in every assisting job.

Before entering the writing phase, think over once again – WHY you need a chatbot? Will it help customer service only? Or will it also help in website navigation, purchase, return, refund, etc.?

Usually, customers want one of the three things when they visit your site: an answer to something they’re looking for, make a purchase, or a solution to their problem. You can custom build your chatbot to tackle either one or all of these three situations. Many brands use chatbots to create tailored products for their clients.  

Cover all possible scenarios

When you start writing the dialogue, consider the fact that a conversation can go in many directions. To ensure that all the situations are covered- start with a flowchart of all possible questions and the answers you chatbot can give.

To further simplify your chatbot writing, take care of one scenario at a time and focus on keeping the conversation short and simple. If the customer is too specific or is not satisfied with the bot’s response, do not hesitate to redirect them to your customer service representatives.

For instance, Xiaocle is one of the most successful interactive chatbots launched by Microsoft in July 2014. Within three months of its launch, Xiaocle accomplished over 0.5 billion conversations. In fact, speakers couldn’t understand that they’re talking to a bot for 10 minutes.

Also read – Why should businesses consider chatbots?

This article is contributed to Mantra Labs by Dorian Martin. Dorian is an established blogger and content writer for business, career, education, marketing, academics, and more.

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The antiquated commodity of Financial ‘Coverage & Protection’ is getting a new make-over.  Conventional epigrams like ‘Insurance is sold and not bought’ are becoming passé. Customers are now more open than ever before to buying insurance as opposed to being sold by an agent.  The industry itself is witnessing an accelerated digitalization momentum on the backs of 4G, Augmented Reality, and Artificial Intelligence-based technologies like Machine Learning & NLP.

As new technologies and consumer habits keep evolving, so are insurance business models. The reality for many insurance carriers is that they still don’t understand their customers with great accuracy and detail, which is where intermediaries like agents and distributors still hold incredible market power.

On the other hand, distribution channels are turning hybrid, which is forcing carriers to be proficient in their entire channel mix. Customer expectations for 2020 will begin to reflect more simplicity and transparency in their mobility & speed of service delivery.

A recently published Gartner Hype Cycle highlights 29 new and emerging technologies that are bound for greater business impact, that will ultimately dissolve into the fabric of Insurance.

For 2020 and beyond, newer technologies are emerging along with older but more progressively maturing ones creating a wider stream of opportunities for businesses.

Gartner-Hype-Cycle

Irrespective of the technology application adopted by insurers — real, actionable insights is the name of the game. Without it, there can be no long term gains. Forrester research explains “Those that are truly insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”.

Based on the major trends identified in the Hype Cycle, 5 of the most near-term disruptive technologies and their use cases, are profiled below.

  1. Emotion AI
    Emotion Artificial Intelligence (AI) is purported to detect insurance fraud based on the audio analysis of the caller. This means that an AI system can decisively measure, understand, simulate and react to human emotions in a natural way.

    F0r Insurers, sentiment and tone analysis captured from chatbots fitted with emotional intelligence can reveal deeper insights into the buying propensity of an individual while also understanding the reasons influencing that decision.

Emotion-Intelligence-Market



Autonomous cars can also sensors, cameras or mics that relay information over the cloud that can be translated into insights concerning the emotional state of the driver, the driving experience of the other passengers, and even the safety level within the vehicle.

Gartner estimates that at least 10% of personal devices will have emotion AI capabilities, either on-device or via the cloud by 2022. Devices with emotion AI capacity is currently around 1%.

  1. Augmented Intelligence
    Augmented Intelligence is all about process intelligence. Widely touted as the ‘future of decision-making’, this technology involves a blend of data, analytics and AI working in parallel with human judgement. If Scripting is rules based automation, then ‘Augmenting’ is engagement and decision oriented.

    This manifests today for most insurance carriers as an automated back-office task, but over the next few years, this technology will be found in almost all internal and customer facing operations. Insurers can potentially offer personalised services based on the client’s individual capacity and exposure to risk — creating opportunities for cross/up-selling.
Gartner-Data-Analytics-Trends-Forecast-2019


Source: Gartner Data Analytics Trends for 2019


For instance, Online Identity Verification is an example of a real-time application that not only enhances human’s decision making ability, but also requires human intervention in only highly critical cases. The Global value from Augmented AI Tools will touch $4 Trillion by 2022.

  1. AR Cloud
    The AR Cloud is simply put a real-time 3D map of an environment, overlayed onto the real World. Through this, experiences and information can be shared without being tied down to a specific location. Placing virtual content using real world coordinates with associated meta-data can be instantly shared and accessed from any device.

    For insurers, there is a wide range of opportunities to entice shopping customers on an AR-Cloud based platform by presenting personalized insurance products relevant to the items they are considering buying.

    The AR ecosystem will be a great way to explain insurance plans to customers, provide training and guidance for employees, assist in real-time damage estimation, improve the quality of ‘moment-of-truth’ engagements. This affords modern insurance products to co-exist seamlessly along the buying journey.

  2. Personification
    Personification is a technology that is wholly dependent on speech and interaction. Through this, people can anthropomorphize themselves and create avatars that can form complex relationships. The Virtual Reality-based concept will be the next way of communicating and forming new interactions.

    VR Applications such as  accident recreation, customer education and live risk assessment, can help insurers lower costs for its customers and personalise the experience.

    Brands have already begun working their way into this space, because as they see it — if younger generations are going to invariably use this technology for longer portions of their day for work, productivity, research, entertainment, even role-playing games, they will shop and buy this way too.

  3. Flying Autonomous Vehicles and Light Cargo Drones
    Although this technology is only a decade away from being commercially realized, the non-flying form is about to make its greatest impact since its original conception. Regulations are the biggest obstacle to the technology taking off, while its functionality continues to improve.

    The Transportation & Logistics ecosystem is on the brink of a complete shift, which will create a demand for a wide array of insurance related products and services that covers autonomous vehicles and cargo delivery using light drones.

While automation continues to bridge the gaps, InsurTechs and Insurance Carriers will need to embrace ahead of the curve and adopt newer strategies to drive sustainable growth.

Mantra Labs is an InsurTech100 company solving complex front & back-office processes for the Digital Insurer. To know more about our products & solutions, drop us a line at hello@mantralabsglobal.com

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